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The XXI century home should be a digital habitat, a connected residence, but at the same time it should be involved in sustainability and the environment. The location of new technologies at home, and its acceptance by the user, requires, among other actions, a significant diffusion and activity to be undertaken. This work proposes the development...
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... Wireless Sensor Networks (WSNs) have many potential applications, which include environmental monitoring, tracking, healthcare, surveillance, smart homes and so forth [1][2][3][4]. Since sensors are battery powered, prolonging the network lifetime of WSNs is crucial for the usage of sensors in this wide range of applications. ...
The data collection problem is one of the most important issues in Wireless Sensor Networks (WSNs). Constructing a tree from all sensor nodes to the sink node is the simplest way, but this raises the problem of energy unbalance since the sensors closer to the sink node would have much higher workloads from relaying data. To cope with the energy unbalance problem, a number of mobile-sink mechanisms have been proposed in recent years. This paper proposes an Energy-Balanced Data Collection mechanism, called EBDC, which determines the trajectory of a mobile data collector (or mobile sink) such that the data-relaying workloads of all sensors can be totally balanced. Theoretical analysis and performance evaluation reveal that the proposed EBDC mechanism outperforms the existing approaches in terms of network lifetime and the degree of energy balancing.
... Now is required to do control across networks and different examples can be found in literature as the PI algorithm with adaptations to work on transmission control protocol (TCP) [15], the effective mobile sensor control method [16] or the wireless control system closed over wireless local area network [17]. We can see how control requirements are not limited to industrial applications; now they can be found in important environmental care applications [18]. ...
Today control is required in any field or application. Nowadays, classic control is the most used, but it is well-known that users need to know the system's characteristics to reach optimal control. This paper is focused on designing a proportional integral derivative control, based on a single artificial neural network with the aim to improve its performance and its use with minimal control knowledge from the end user. The proposed control was assessed with simulated and practical physical systems of first and second order. In order to increase the confidence of the intelligent sensor control, the evaluation was made using the classical test of control response of a step as input. The proposed control was implemented on an intelligent sensor with a small microcontroller. Also, the performance was compared between the proposed control and a commercial control. Here, an intelligent sensor is presented with control capability for a wide variety of physical systems. The experiments performed demonstrated the capability of the proposed control, which can be easily used and save time at the initial control set up.
... 1). The house integrates sustainable elements based on renewable energies, self-sufficiency energetic methods, bioclimatic architecture and recycled construction materials [20]. It includes PV generation, electricity storage through batteries, a set of automated appliances and a connection to the grid [21]. ...
In this paper, we describe the development of a control system for Demand-Side Management in the residential sector with Distributed Generation. The electrical system under study incorporates local PV energy generation, an electricity storage system, connection to the grid and a home automation system. The distributed control system is composed of two modules: a scheduler and a coordinator, both implemented with neural networks. The control system enhances the local energy performance, scheduling the tasks demanded by the user and maximizing the use of local generation.
... The electric self-sufficiency of " MagicBox " is based on consuming the maximum amount of energy at the same time it is produced, by means of a suitable control system. Moreover, the exploitation of its bioclimatic design reduces the energy needs to achieve adequate comfort levels inside the house [12]. It is an example of added value for PV electricity which arises from the combination of modern hybrid PV technology with a lead-acid battery storage system and DSM strategies in the residential sector. ...
In this paper we present a heterogeneous collaborative sensor network for electrical management in the residential sector. Improving demand-side management is very important in distributed energy generation applications. Sensing and control are the foundations of the "Smart Grid" which is the future of large-scale energy management. The system presented in this paper has been developed on a self-sufficient solar house called "MagicBox" equipped with grid connection, PV generation, lead-acid batteries, controllable appliances and smart metering. Therefore, there is a large number of energy variables to be monitored that allow us to precisely manage the energy performance of the house by means of collaborative sensors. The experimental results, performed on a real house, demonstrate the feasibility of the proposed collaborative system to reduce the consumption of electrical power and to increase energy efficiency.
... The electric self-sufficiency of "MagicBox" is based on consuming the maximum amount of energy at the same time it is produced, by means of a suitable control system. Moreover, the exploitation of its bioclimatic design reduces the energy needs to achieve adequate comfort levels inside the house [12]. It is an example of added value for PV electricity which arises from the combination of modern hybrid PV technology with a lead-acid battery storage system and DSM strategies in the residential sector. ...
The AURA 1.0 prototype is a sustainable social housing proposal, designed by the University of Seville and built for the first Latin American edition of the prestigious Solar Decathlon competition. Different conditioning strategies were integrated into this prototype, optimized for a tropical climate, and focused on contributing positively to the health of the most humble people in society. In this moment, in which a large part of the world population is confined to their homes due to the Covid-19 pandemic, we have the opportunity (and the obligation) to reconsider the relationship between architecture and medicine or in other words, between the daily human habitat and health. For this reason, this analysis of aspects derived from the interior conditioning of the homes is carried out. The main objective of the Aura proposal is to be able to extract data through a housing monitoring system, which allows us to transfer some design strategies to the society to which is a case study, in order to promote environmental comfort and, therefore, people’s health. The AURA 1.0 prototype develops flexible and adaptable living spaces, with a high environmental quality, in order to maintain the variables of temperature, relative humidity and natural lighting within a range of comfort required by the rules of the event. To achieve this end, the prototype develops an architectural proposal that combines passive and active conditioning strategies, using construction qualities and typical costs of social housing. These strategies allowed the project to achieve the first prize in the Comfort Conditions test. So, this paper presents an appropriate and tested solution that can satisfy comfortability and health of residents who live in social housing while maintaining low energy consumption.
In this paper, the design and implementation process of an artificial neural network based predictor to forecast a day ahead of the power consumption of a building HVAC system is presented. The featured HVAC system is situated at MagicBox, a real self-sufficient solar house with a monitoring system. Day ahead prediction of HVAC power consumption will remarkably enhance the Demand Side Management techniques based on appliance scheduling to reach defined goals. Several multi step prediction models, based on LSTM neural networks, are proposed. In addition, suitable data preprocessing and arrangement techniques are set to adapt the raw dataset. Considering the targeted prediction horizon, the models provide outstanding results in terms of test errors (NRMSE of 0.13) and correlation, between the temporal behavior of the predictions and test time series to be forecasted, of 0.797. Moreover, these results are compared to the simplified one hour ahead prediction that reaches nearly optimal test NRMSE of 0.052 and Pearson correlation coefficient of 0.972. These results provide an encouraging perspective for real-time energy consumption prediction in buildings.
Realization of open online control of diverse in-situ sensors is a challenge. This paper proposes a Cyber-Physical Geographical Information Service-enabled method for control of diverse in-situ sensors, based on location-based instant sensing of sensors, which provides closed-loop feedbacks. The method adopts the concepts and technologies of newly developed cyber-physical systems (CPSs) to combine control with sensing, communication, and computation, takes advantage of geographical information service such as services provided by the Tianditu which is a basic geographic information service platform in China and Sensor Web services to establish geo-sensor applications, and builds well-designed human-machine interfaces (HMIs) to support online and open interactions between human beings and physical sensors through cyberspace. The method was tested with experiments carried out in two geographically distributed scientific experimental fields, Baoxie Sensor Web Experimental Field in Wuhan city and Yemaomian Landslide Monitoring Station in Three Gorges, with three typical sensors chosen as representatives using the prototype system Geospatial Sensor Web Common Service Platform. The results show that the proposed method is an open, online, closed-loop means of control.
This paper presents the operation of an Electrical Demand-Side Management (EDSM) system in a real solar house. The use of EDSM is one of the most important action lines to improve the grid electrical efficiency. The combination between the EDSM and the PV generation performs a new control level in the local electric behavior and allows new energy possibilities. The solar house used as test-bed for the EDSM system owns a PV generator, a lead-acid battery storage system and a grid connection. The electrical appliances are controllable from an embedded computer. The EDSM is implemented by a control system which schedules the tasks commanded by the user. By using the control system, we define the house energy policy and improve the energy behavior with regard to a selected energy criterion, self-consumption. The EDSM system favors self-consumption with regard to a standard user behavior and reduces the energy load from the grid.
